ARB Security Solutions, LLC.

Exchange Online and PyTorch To Perform Sentiment Analysis On Bodies and Recommendations

Whole lotta assumptions here but whatever. After retrieving the email bodies using Exchange Online, the Python code loads the sentiment analysis model and the email response recommendation model. It then processes the email bodies and generates response recommendations using the GPT-2 model. The sentiment analysis results and the response recommendations are printed for each email body.

# Install required PowerShell modules if not already installed
if (-not (Get-Module -ListAvailable -Name ExchangeOnlineManagement)) {
    Install-Module -Name ExchangeOnlineManagement -Force -AllowClobber
}

# Import the required modules
Import-Module ExchangeOnlineManagement

# Connect to Exchange Online
Connect-ExchangeOnline -Credential (Get-Credential)

# Retrieve a list of email bodies
$mails = Get-EXOMailboxMessage -ResultSize 100

# Import the required PyTorch modules
$pythonCode = @"
import torch
from transformers import pipeline

# Load the sentiment analysis model
sentiment_model = pipeline('sentiment-analysis')

# Load the email response recommendation model
recommendation_model = torch.hub.load('huggingface/transformers', 'text-generation', 'gpt2')

# Process email bodies and generate response recommendations
email_bodies = [
    " $($mails.Body -join '" "') "
]

sentiment_results = sentiment_model(email_bodies)

response_recommendations = []

# Generate response recommendations for each email body
for body in email_bodies:
    # Preprocess email body (e.g., cleaning, tokenization)

    # Generate response recommendation using the GPT-2 model
    recommendation = recommendation_model(body, max_length=50, num_return_sequences=3)

    response_recommendations.append(recommendation)

# Output the sentiment analysis and response recommendations
for i in range(len(email_bodies)):
    print('Email Body:', email_bodies[i])
    print('Sentiment:', sentiment_results[i]['label'], sentiment_results[i]['score'])
    print('Response Recommendations:')
    for j, recommendation in enumerate(response_recommendations[i]):
        print(f'Recommendation {j+1}: {recommendation["generated_text"]}')
    print('---')
"@

# Run the Python code using the Python executable
$output = & python -c $pythonCode

# Output the sentiment analysis and response recommendations
Write-Output $output

# Disconnect from Exchange Online
Disconnect-ExchangeOnline

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